Unsupervised Detection of High-Frequency Oscillations Using Time-Frequency Maps and Computer Vision.

ABSTRACT: High-frequency oscillations >80 Hz (HFOs) have unique features distinguishing them from spikes and artifactual components that can be well-evidenced in the time-frequency representations. We introduce an unsupervised HFO detector that uses computer-vision algorithms to detect HFO landmarks on two-dimensional (2D) time-frequency maps. To validate the detector, we introduce an analytical model of the HFO based on a sinewave having a Gaussian envelope, for which analytical equations in time-frequency space can be derived, allowing us to establish a direct correspondence between common HFO detection criteria in the time domain with the ones in the frequency domain, used by the computer-vision detection algorithm. The detector identifies potential HFO events on the time-frequency representation

SUBMITTER: Donos C 

PROVIDER: S-EPMC7104802 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature